Data Analytics Fundamentals

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18 Questions

What is the primary purpose of data analytics in commercial industries?

To make business decisions and optimize performance

What is the process of gaining valuable insights from data to make effective business decisions called?

Data Analysis

What type of analytics involves using data to predict future outcomes?

Predictive analytics

Who are responsible for performing data analytics tasks?

Data Analysts and Data Engineers

What is the term for the process of transforming data into a more usable format?

Data Transformation

What is the primary goal of data visualization?

To get better perception of datasets

What is a crucial requirement for a scale in data visualization?

It must be a one-to-one mapping

What type of scale is suitable for data that exhibits exponential growth?

Logarithmic scale

What is the purpose of a scale in data visualization?

To map data values onto aesthetic values

What type of coordinate system is commonly used for circular data?

Polar coordinate system

What is the primary characteristic of the angle axis in the polar coordinate system?

Circular

What is the result of using a scale that is not one-to-one?

A more ambiguous data visualization

Which type of data analysis involves understanding the relationships between variables?

Multivariate analysis

What is an example of a data transformation?

Applying a logarithmic scale to the data

What is the purpose of data transformation in the context of data analysis?

To stabilize the variance of continuous data

What is the primary advantage of using logarithmic scales in data visualization?

They can be used to visualize nonlinear relationships

What is the main difference between categorical and continuous data?

Categorical data is qualitative, while continuous data is quantitative

What is the coordinate system used to specify positions via an angle and a radial distance from the origin?

Polar coordinate system

Study Notes

Data Types and Visualization

  • A dataset can have various types of data, including:
    • Ordered factor (e.g., month)
    • Discrete numerical value (e.g., day)
    • Unordered factor (e.g., location, station ID)
    • Continuous numerical value (e.g., temperature in degrees Fahrenheit)

Data Visualization and Scales

  • Scales map data values to aesthetic values (e.g., x-axis positions, shapes, colors)
  • A scale must be one-to-one, ensuring a unique mapping between data and aesthetics values
  • In polar coordinate systems, positions are specified via an angle and radial distance from the origin

Data Analysis Tasks

  • Importing datasets and libraries (e.g., numpy, pandas, matplotlib, seaborn)
  • Importing a dataset (e.g., Credit Card Approvals) using pd.read_csv()

Data Characteristics

  • Categorical data: Gender, Married, BankCustomer, Industry, Ethnicity, PriorDefault, Employed, DrivingLicense, Citizen, Approved
  • Continuous data: Age, Debt, YearsEmployed, CreditScore, Income

Univariate Analysis

  • Univariate analysis is a basic form of data analysis, focusing on a single variable
  • Used to understand the data without examining causes or effects relationships

Data Analytics

  • Data analytics: the process of analyzing data sets to make informed decisions
  • Uses specialized software and systems to help businesses:
    • Understand customers better
    • Improve advertising campaigns
    • Personalize content
    • Improve bottom lines

Data Visualization and Analytics

  • Data visualization helps gain better insights into data
  • Both data visualization and analytics draw conclusions about datasets
  • Data visualization can be static or interactive

Test your understanding of data analytics, its applications, and techniques in commercial industries. Learn how data analytics can help businesses make informed decisions, improve customer understanding, and boost their bottom lines.

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